Course: STAT 27420
Title: Introduction to Causality with Machine Learning
Instructor(s): Victor Veitch
Teaching Assistant(s): Yu Gui
Class Schedule: Sec 1: TR 3:30 PM-4:50 PM in E312
Description: This course is an introduction to causal inference. We'll cover the core ideas of causal inference and what distinguishes it from traditional observational modeling. This includes an introduction to some foundational ideas---structural equation models, causal directed acyclic graphs, and then do calculus. The course has a particular emphasis on the estimation of causal effects using machine learning methods.